Space-Time Adaptation for Patch-Based Image Sequence Restoration
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
A new fuzzy-based wavelet shrinkage image denoising technique
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
De-noising by soft-thresholding
IEEE Transactions on Information Theory
Highly scalable wavelet-based video codec for very low bit-rate environment
IEEE Journal on Selected Areas in Communications
IEEE Transactions on Image Processing
Fast motion vector estimation using multiresolution-spatio-temporal correlations
IEEE Transactions on Circuits and Systems for Video Technology
Combined spatial and temporal domain wavelet shrinkage algorithm for video denoising
IEEE Transactions on Circuits and Systems for Video Technology
Wavelet-Domain Video Denoising Based on Reliability Measures
IEEE Transactions on Circuits and Systems for Video Technology
Video Denoising Based on Inter-frame Statistical Modeling of Wavelet Coefficients
IEEE Transactions on Circuits and Systems for Video Technology
Efficient video denoising based on dynamic nonlocal means
Image and Vision Computing
Differential evolution algorithm for motion estimation
MIWAI'11 Proceedings of the 5th international conference on Multi-Disciplinary Trends in Artificial Intelligence
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Integrating video coding and denoising is a novel processing paradigm, bringing mutual benefits to both video processing tools. In this paper, we propose a novel video denoising approach of which the main idea is reusing motion estimation resources from the video coding module for video denoising. In most cases, the motion fields produced by real-time video codecs cannot be directly employed in video denoising, since they, as opposed to noise filters, tolerate errors in the motion field. In order to solve this problem, we propose a novel motion-field filtering step that refines the accuracy of the motion estimates to a degree that is required for denoising. Additionally, a novel temporal filter is proposed that is robust against errors in the estimated motion field. Numerical results demonstrate that the proposed denoising scheme is of low-complexity and compares favorably to the state-of-the-art video denoising methods.